Controlled clinical trials最新文献

Before any clinical trial can begin to recruit patients, participating clinical centers must obtain approval from their institutional review board (IRB). When studies are federally funded, such as by the U.S. Department of Health and Human Services (DHHS), centers must also have or obtain a federal compliance agreement from the Office of Human Research Protections (formerly the Office for Protection from Research Risks [OPRR]). The Digitalis Investigation Group trial was a large, international, double-blind, DHHS-funded randomized trial on the effect of digoxin on mortality in heart failure. Due to the anticipated number of centers (>200), the study's data coordinating center (DCC) was requested to assume additional responsibilities that included: (1) acting as a liaison between the OPRR and all study centers; (2) reviewing and correcting all assurance statements before submission to the OPRR; (3) reviewing and approving all centers' informed consent forms; and (4) helping the many research-inexperienced centers to establish IRBs or to locate an IRB in their region that would accept IRB responsibility for them. Although a heavy burden was placed on the DCC, the IRB and OPRR approval process was probably shortened by many weeks at those centers not already possessing a federal compliance agreement. This enabled the study to be completed on schedule and within budget.

Large simple trials (LSTs) emerged in response to the need for large sample sizes to answer important clinical questions in which treatments have a moderate effect on clinical endpoints. Between 1991 and 1996 the National Heart, Lung, and Blood Institute and the Department of Veterans Affairs (VA) Cooperative Studies Program conducted an LST entitled “Digitalis Investigation Group (DIG): Trial to Evaluate the Effect of Digitalis on Mortality in Heart Failure.” The VA Cooperative Studies Program Clinical Research Pharmacy Coordinating Center served as the DIG pharmacy coordinating center (PCC). As a direct result of involvement in the DIG trial, the PCC identified the need for an increased emphasis on computerization and automated support of clinical trials, especially LSTs.

For various diseases clinicians have to combine different drugs or interventions when a single drug or intervention does not lead to satisfactory results. However, quantifying the relative benefit of certain drugs or interventions when given alone and in combination under controlled conditions requires a complex factorial design. This paper describes such a method applied to a large multicenter trial for the prevention of postoperative nausea and vomiting (PONV), which may be of great interest for other specialties. Approximately 28 million operations are performed annually in the United States, mainly under general anesthesia with volatile anesthetics. Unfortunately, one-third of these patients suffer from PONV. This prompted extensive research of antiemetic and anesthetic drugs, but none of the interventions appeared to satisfactorily prevent PONV. Scuderi et al. were the first to almost eliminate PONV by combining various antiemetic interventions; however, the relative benefit of each intervention remained unclear. Accordingly, we have designed a large randomized controlled trial studying six different antiemetic interventions—three involving use of various antiemetic drugs and three involving choice of anesthetic drugs—to answer the following main questions: (1) What is the relative benefit of each of the antiemetic intervention? (2) Are certain combinations of antiemetic interventions more effective than others? Using a complete factorial design this leads to 2³ = 8 antiemetic combinations, which multiply with the 2³ = 8 combinations of anesthetic drugs, leading to a total of 2⁶ = 64 possible combinations. The six factors are the antiemetics ondansetron (versus control), dexamethasone (versus control), droperidol (versus control), and the intravenous anesthetic propofol (versus volatile anesthetics), air (versus nitrous oxide), and remifentanil (versus fentanyl). The primary outcome is freedom from PONV within the first 24 hours after anesthesia. Eligible patients are adults scheduled for elective surgery under general anesthesia with an increased risk for PONV so that the expected incidence in the control group (with none of the six antiemetic interventions) is approximately 60%. In order to allow analyses for up to three factor interactions, a sample size was estimated to be in the range of approximately 5000 patients. To the best of our knowledge this is the first randomized controlled trial of a six-way factorial design that may serve as an example for numerous other medical specialties.

The Digitalis Investigation Group (DIG) trial was a large simple trial (LST) begun in 1990 as a collaboration between the National Heart, Lung, and Blood Institute and the Department of Veterans Affairs (VA) Cooperative Studies Program (CSP). Its primary objective was to determine whether digitalis had beneficial, harmful, or no effect on total mortality in patients with congestive heart failure and an ejection fraction ≤0.45. The Perry Point VA CSP Coordinating Center served as the trial's data coordinating center (DCC). The DCC was involved in all phases of the study from planning and design, organization and start-up, and patient recruitment and follow-up through closeout, final analyses, and manuscript preparation. While DCC responsibilities for an LST are basically the same as for other multicenter randomized clinical trials, their size and the inclusion of many inexperienced research sites can add a complexity that the DCC must be prepared to handle from the beginning. This paper describes the role of the DCC in the DIG trial.

In the analysis of survival data arising in clinical trials, Cox's proportional hazards regression model (or equivalently in the case of two treatment groups, the log-rank test) is firmly established as the accepted, statistical norm. The wide popularity of this model stems largely from extensive experience in its application and the fact that it is distribution free—no assumption has to be made about the underlying distribution of survival times to make inferences about relative death rates. However, if the distribution of survival times can be well approximated, parametric failure-time analyses can be useful, allowing a wider set of inferences to be made. The Weibull distribution is unique in that it is the only one that is simultaneously both proportional and accelerated so that both relative event rates and relative extension in survival time can be estimated, the latter being of clear clinical relevance. The aim of this paper is to examine the use and utility of the Weibull model in the analysis of survival data from clinical trials and, in doing so, illustrate the practical benefits of a Weibull-based analysis.

The Italian-American Clinical Trial of Nutritional Supplements and Age-Related Cataract (CTNS) is a 13-year study designed primarily to evaluate the safety and efficacy of a vitamin-mineral supplement containing recommended daily allowance (RDA) dosages in preventing age-related cataract or delaying its progression. As secondary objectives the study will collect data on incidence and progression rates as well as risk factors for the disease. The clinical trial was initiated largely because of epidemiological studies suggesting that various nutrients, particularly those with antioxidant capabilities, might retard cataract development. The possibility of a beneficial effect on cataract and other age-related diseases has contributed to the widespread use of dietary supplements in the United States among the elderly population, even in the absence of definitive evidence about the safety and effectiveness of such use. The low rate of dietary supplement use in the Italian population provided an opportunity for a trial in which the efficacy of RDA dose supplementation could be tested against no supplementation at all. Relevant design issues for the study include defining cataract and cataract progression, estimating event rates, evaluating reproducibility of the lens grading system for different types of opacity, and identifying the criteria for assessing efficacy and safety. This paper describes the CTNS design and rationale and the approach used to address the issues described above.

We present a phase I design that is a modification to the time-to-event continual reassessment method (TITE-CRM) by Cheung and Chappell that is useful when each dose actually denotes how long a drug is administered. Because of the lengthy duration required for subjects receiving the higher doses, we enroll each subject on the best estimate of the maximum tolerated cumulative dose (MTCD) as soon as each subject is eligible. Once each previously enrolled subject is fully evaluated, we update our estimate of the MTCD and modify currently enrolled subjects to receive the MTCD if they are currently receiving a nonoptimal dose. Thus, our method is adaptive both between subjects and within subjects. We show through simulation that our study design has excellent operating characteristics that are as good as the TITE-CRM while not exposing greater numbers of subjects to doses beyond the MTCD. Our simulations are based upon a study in bone marrow transplant patients that seeks to determine how many weeks of recombinant human keratinocyte growth factor can be administered while keeping toxicity rates below a desired threshold.

Even the best-designed, randomized controlled trials suffer when patients are lost to follow-up. Incomplete follow-up biases the results of a trial when patients who drop out are different from those who complete follow-up. This is exaggerated further when there are differential dropout rates between study groups. Previous randomized controlled trials in orthopedic trauma have reported up to 28% loss to follow-up. Only by striving to achieve a 0% loss to follow-up rate can we be certain that this type of bias does not affect our results. In our ongoing multicenter, randomized controlled trial comparing reamed and nonreamed intramedullary nailing of tibial shaft fractures, we have implemented several innovative strategies to minimize loss to follow-up. The exclusion criteria and consent process are designed to minimize losses. Study staff are carefully trained in communication and negotiation with patients. Additionally, a central methods center monitors all patient follow-up and aids in finding lost patients. Through these primary, secondary, and tertiary interventions, we have achieved 94% complete 1-year follow-up for the first 440 patients enrolled in the trial. Eleven patients withdrew consent, and we are unable to locate 17 patients. We have successfully minimized the loss to follow-up rate in our trial by incorporating innovative prevention and retention strategies into its design and conduct. Through planning, organization, and committing time and resources to minimizing loss to follow-up, other orthopedic trauma trials can hope to achieve the same high rates of follow-up.